DOCSLIB.ORG

A Brief History of Graphs

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
A Brief History of Graphs A brief history of graphs. Data is presented in graphs as information is easier to retain visually than as numbers or tables. This has been recognised for over 200 years. William Playfair, who is acknowledged as the creator of the bar and pie graphs in 1786 and 1801, stated that ‘Information, that is imperfectly acquired, is generally as imperfectly retained; and a man who has carefully investigated a printed table, finds, when done, that he has only a very faint and partial idea of what he has read; and like a figure imprinted on sand, is soon totally erased and defaced.’ (Playfair, The Commercial and Political Atlas, 1786). Examples of Playfair’s graphs: Playfair's trade-balance time-series chart (Playfair, Commercial and Political Atlas, 1786) Proportions of the Turkish Empire located in Asia, Europe and Africa before 1789 (Playfair, Statistical Breviary, 1801) 1 Two early graphics that were the basis of policy change were John Snow’s 1854 ‘Broad Street Map’ which was used to locate the origin (the Board Street Pump) of an outbreak of cholera in London and the 1858 ‘Rose’ of Florence Nightingale, a diagram of the causes of death in the Crimean war that showed that most soldiers were dying from preventable diseases not war injuries. Small (1998) suggests that while Florence Nightingale was not the first person to use graphics to present statistics ‘she may have been the first to use them for persuading people of the need for change’. John Snow’s Map of Board Street Cholera deaths: Florence Nightingale’s Rose (reproduced from Small, 1988) 2 A short video about Nightingale’s Rose is available at http://www.bbc.co.uk/programmes/p00chk4w. Today, many graphs are available as dynamic visualisations (able to be played over time) and a dynamic version of Nightingales’ Rose is available at http://understandinguncertainty.org/nightingale. Many of the types of graphs shown above are still in use today and can be created in Excel. For example, Pie graphs are regularly used to look at the likely proportions of votes from opinion poll data. Example: February 17, 2006 TVNZ Colmar Brunton Poll 1% 1% Percentage of Vote 3% 2% 6% 53% 34% National Labour Greens Maori NZ First ACT Other Bar charts (histograms and box plots) are still routinely used to compare data distributions for different groups as in the following example that looks at different travel preferences in two New Zealand cities. Example: (Statistics New Zealand, Census 2006) A particular type of line graph, a time series, is a simple but powerful graph often used for looking at trends for different groups across time, as in the example below that shows unemployment rates by highest educational qualification in New Zealand. 3 Example: Statistics New Zealand, Household Employment Survey Quarterly NZ Unemployment Rates by Highest Education Qualification Percent 20.0 No School Post School School 15.0 10.0 5.0 0.0 Mar 86 Mar 87 Mar 88 Mar 89 Mar 90 Mar 91 Mar 92 Mar 93 Mar 94 Mar 95 Mar 96 Mar 97 Mar 98 Mar 99 Mar 00 Mar 01 Mar 02 Mar 03 Mar 04 Mar 05 Mar 06 Mar 07 Quarter Simple graphs that can be created in Excel are sometimes displayed with multiple graphs as in the following examples. Dashboards show many indicators simultaneously. Tableaus show the same indicator in multiple groups. Source: Statistics New Zealand 4 Many recent graphs that extend those that can be created in Excel have dynamic (play over time) and interactive features. Dynamic population pyramids and other interactive graphs are now routinely used by many national statistics offices (e.g. http://www.stats.govt.nz/tools_and_services/interactive-pop-pyramid.aspx an http://www.china-profile.com/data/ani_ceu_pop.htm). Possibly the best known dynamic and interactive graph is Hans Rosling’s Gapminder (www.gapminder.org) that uses bubble graphs to display five variables simultaneously: region (colour), relative population size of a country (size of bubble), two other variables chosen from a set of OECD indicators (on the vertical and horizontal axes) and time (as the dynamic variable). Some of the interactive features of Gapminder are shown below. Rosling (2010) suggested that the exploration of data using these graphs raises new policy questions and also challenges old ‘myths’. Select between Click here for Click here to get a short Click here if you are using Chart and Map a short tutorial link to the specific the graph in a lecture. The view. video. graph you have created. graph will cover the whole screen. Click here to Countries select indicators on the for the y axis. graph are Hover mouse colour over bubble to coded by reveal country name. continent. If you want You can information colour about the code by sources you other can click on indicators the small . Click here to open a tool that Select text next to helps you zoom in or out. Click individual the axis. 100% to see the whole graph countries again. Change size of the thebubbles bubbles Both the x Watch the graph and y axis Change the speed Click here to select Click Trails to track change over time scales can of the graph here. indicators for the x axis. a selected country by using these be linear or You can also choose to while an animation buttons . logarithmic. display time on this axis. plays. Choosing a log scale Adapted from an original idea by may make it wwww.juicygeography.co.uk easier to see the trends on the 5 graph. Even with static (non-moving graphs), creativity is a feature of many modern graphics, although many of these require more sophisticated graphing tools than Excel to create. Examples include Hidaglo’s tubular ‘Development Tree’ displaying the Human Development Index (HDI) for any country (Hidaglo, 2010). Hidaglo’s Tubular tree representation of the Human Development Index (HDI) The HDI representation for any country can be created at (http://chidalgo.com/Gallery/HDR2010/DevelopmentTreeApplications.zip) as in the example below. Hidaglo’s HDI, 1975-2005 for Egypt (top) and New Zealand (bottom) 1975 1985 1995 2005 1975 1985 1995 2005 Another example is the Organization for Economic Co-operation and Development (OECD) ‘floral’ representation (the Better Life Index) that allows for quick comparisons between countries on a set of socio-economic indicators http://www.oecdbetterlifeindex.org/. 6 Example: New Zealand’s Better Life Index (2011) The use of graphs and the display of geographic data in maps is increasing rapidly, in particular in the media, as more and bigger datasets become available. The following example shows how a large data set of people’s movement from work to home (commuting patterns) in New Zealand can be displayed effectively on a map. Graphs and maps are now being integrated with using Geographic Information Systems (GIS) software. However, as more and more graphs are produced we need to be sure that they are based on good, rather than bad, data and that the graph accurately represents the data. 7 .
Load more

Recommended publications
  • Milestones in the History of Data Visualization
    Milestones in the History of Data Outline Visualization • Introduction A case study in statistical historiography – Milestones Project: overview {flea bites man, bites flea, bites man}-wise – Background Michael Friendly, York University – Data and Stories CARME 2003 • Milestones tour • Problems of statistical historiography – What counts as a milestone? – What is “data” – How to visualize? Milestones: Project Goals Milestones: Conceptual Overview • Comprehensive catalog of historical • Roots of Data Visualization developments in all fields related to data – Cartography: map-making, geo-measurement visualization. thematic cartography, GIS, geo-visualization – Statistics: probability theory, distributions, • o Collect representative bibliography, estimation, models, stat-graphics, stat-vis images, cross-references, web links, etc. – Data: population, economic, social, moral, • o Enable researchers to find/study medical, … themes, antecedents, influences, patterns, – Visual thinking: geometry, functions, mechanical diagrams, EDA, … trends, etc. – Technology: printing, lithography, • Web: http://www.math.yorku.ca/SCS/Gallery/milestone/ computing… Milestones: Content Overview Background: Les Albums Every picture has a story – Rod Stewart c. 550 BC: The first world map? (Anaximander of Miletus) • Album de 1669: First graph of a continuous distribution function Statistique (Gaunt's life table)– Christiaan Huygens. Graphique, 1879-99 1801: Pie chart, circle graph - • Les Chevaliers des William Playfair 1782: First topographical map- Albums M.
    [Show full text]
  • An Investigation Into the Graphic Innovations of Geologist Henry T
    Louisiana State University LSU Digital Commons LSU Doctoral Dissertations Graduate School 2003 Uncovering strata: an investigation into the graphic innovations of geologist Henry T. De la Beche Renee M. Clary Louisiana State University and Agricultural and Mechanical College Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_dissertations Part of the Education Commons Recommended Citation Clary, Renee M., "Uncovering strata: an investigation into the graphic innovations of geologist Henry T. De la Beche" (2003). LSU Doctoral Dissertations. 127. https://digitalcommons.lsu.edu/gradschool_dissertations/127 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Doctoral Dissertations by an authorized graduate school editor of LSU Digital Commons. For more information, please [email protected]. UNCOVERING STRATA: AN INVESTIGATION INTO THE GRAPHIC INNOVATIONS OF GEOLOGIST HENRY T. DE LA BECHE A Dissertation Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Doctor of Philosophy in The Department of Curriculum and Instruction by Renee M. Clary B.S., University of Southwestern Louisiana, 1983 M.S., University of Southwestern Louisiana, 1997 M.Ed., University of Southwestern Louisiana, 1998 May 2003 Copyright 2003 Renee M. Clary All rights reserved ii Acknowledgments Photographs of the archived documents held in the National Museum of Wales are provided by the museum, and are reproduced with permission. I send a sincere thank you to Mr. Tom Sharpe, Curator, who offered his time and assistance during the research trip to Wales.
    [Show full text]
  • STAT 6560 Graphical Methods
    STAT 6560 Graphical Methods Spring Semester 2009 Project One Jessica Anderson Utah State University Department of Mathematics and Statistics 3900 Old Main Hill Logan, UT 84322{3900 CHARLES JOSEPH MINARD (1781-1870) And The Best Statistical Graphic Ever Drawn Citations: How others rate Minard's Flow Map of Napolean's Russian Campaign of 1812 . • \the best statistical graphic ever drawn" - (Tufte (1983), p. 40) • Etienne-Jules Marey said \it defies the pen of the historian in its brutal eloquence" -(http://en.wikipedia.org/wiki/Charles_Joseph_Minard) • Howard Wainer nominated it as the \World's Champion Graph" - (Wainer (1997) - http://en.wikipedia.org/wiki/Charles_Joseph_Minard) Brief background • Born on March 27, 1781. • His father taught him to read and write at age 4. • At age 6 he was taught a course on anatomy by a doctor. • Minard was highly interested in engineering, and at age 16 entered a school of engineering to begin his studies. • The first part of his career mostly consisted of teaching and working as a civil engineer. Gradually he became more research oriented and worked on private research thereafter. • By the end of his life, Minard believed he had been the co-inventor of the flow map technique. He wrote he was pleased \at having given birth in my old age to a useful idea..." - (Robinson (1967), p. 104) What was done before Minard? Examples: • Late 1700's: Mathematical and chemical graphs begin to appear. 1 • William Playfair's 1801:(Chart of the National Debt of England). { This line graph shows the increases and decreases of England's national debt from 1699 to 1800.
    [Show full text]
  • Master Thesis SC Final
    The Potential Role for Infographics in Science Communication By: Laura Mol (2123177) Biomedical Sciences Master Thesis Communication specialization (9 ECTS) Vrije Universiteit Amsterdam Under supervision of dr. Frank Kupper, Athena Institute, Vrije Universiteit Amsterdam November 2011 Cover art: ‘Nonsensical Infograhics’ by Chad Hagen (www.chadhagen.com) "Tell me and I'll forget; show me and I may remember; involve me and I'll understand" - Chinese proverb - 2 Index !"#$%&'$()))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))(*! "#!$%&'()*+&,(%())))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))(+! ,),! !(#-.%$(-/#$.%0(.1(#'/23'2('.4453/'&$/.3())))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))(6! ,)7! 8#/39(/4&92#(/3(#'/23'2('.4453/'&$/.3()))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))(:! -#!$%.(/'012,+3()))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))(,;! 7),! <3$%.=5'$/.3())))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))(,;! 7)7! >/#$.%0()))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))(,,! 7)?! @/112%23$(AB2423$#())))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))(,:! 7)*! C5%D.#2()))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))(,:!
    [Show full text]
  • Lecture Slides
    MTTTS17 Dimensionality Reduction and Visualization Spring 2020 Jaakko Peltonen Lecture 4: Graphical Excellence Slides originally by Francesco Corona 1 Outline Information visualization Edward Tufte The visual display of quantitative information Graphical excellence Data maps Time series Space-time narratives Relational graphics Graphical integrity Distortion in data graphics Design and data variation Visual area and numerical measure 2 Information visualization Data graphics visually display measured quantities by means of the combined use of points, lines, a coordinate system, numbers, words, shading and colour The use of abstract, non-representational pictures to show numbers is a surprisingly recent invention, perhaps because of the diversity of skills required: - visual-artistic, empirical-statistical, and mathematical It was not until 1750-1800 that statistical graphics were invented, long after Cartesian coordinates, logarithms, the calculus, and the basics of probability theory William Playfair (1759-1823) developed/improved upon (nearly) all fundamental graphical designs, seeking to replace conventional tables of numbers with systematic visual representations A Scottish engineer and a political economist The founder of graphical methods of statistics A pioneer of information graphics 3 Information visualization (cont.) Modern data graphics can do much more than simply substitute for statistical tables Graphics are instruments for reasoning about quantitative information Often, the most effi cient way to describe, explore, and summarize
    [Show full text]
  • STAT 6560 Graphical Methods
    STAT 6560 Graphical Methods Spring Semester 2009 Project Work James B. Odei Utah State University Department of Mathematics and Statistics 3900 Old Main Hill Logan, UT 84322{3900 WILLIAM PLAYFAIR (1759-1823) A Graphical Pioneer of the 18th Century Citations: How others rate William Playfair . • \the father of modern graphical display" - (Wainer (2005), p. 5) • \the great pioneer of statistical graphics" - (Playfair (2005), p. v) • \the founder of graphical methods of statistics"-(http://en.wikipedia.org/ wiki/William_Playfair) • \the inventor of statistical graphs and writer on political economy" - (Spence (2004), http://www.oxforddnb.com/view/printable/22370) • \the pioneer of information graphics"-(http://en.wikipedia.org/wiki/William_ Henry_Playfair) • \an engineer, political economist and scoundrel" - (Spence and Wainer in Statis- ticians of the Centuries, http://bibleproupdate2.com/Definitions/William_ Playfair) • \an ingenious mechanic and miscellaneous writer" - (Eminent Scotsmen, http: //bibleproupdate2.com/Definitions/William_Playfair) Brief background • Born on September 22, 1759. • Was the fourth son of the Reverend James Playfair of the parish of Liff & Benvie near the city of Dundee, Scotland. • Much of his early education was the responsibility of his brother John Playfair (1748-1819), a professor of mathematics and natural philosophy at Edinburgh University. • He pursued variety of careers with such passion, ambition, industry, and optimism that even without his great innovations he would be judged a colorful figure. 1 • He was in turn apprenticed (1774-1747) under Andrew Meikle(inventor of the threshing machine ), millwright to the Rennie family, draftsman for James Watt (inventor of the steam engine), engineer, accountant, inventor, silversmiths, mer- chant, investment broker, economist, statistician, pamphleteer, translator, pub- licist, land speculator, convict, banker, ardent royalist, editor, blackmailer, and journalist.
    [Show full text]
  • No Humble Pie: the Origins and Usage of a Statistical Chart
    Journal of Educational and Behavioral Statistics Winter 2005, Vol. 30, No. 4, pp. 353–368 No Humble Pie: The Origins and Usage of a Statistical Chart Ian Spence University of Toronto William Playfair’s pie chart is more than 200 years old and yet its intellectual ori- gins remain obscure. The inspiration likely derived from the logic diagrams of Llull, Bruno, Leibniz, and Euler, which were familiar to William because of the instruction of his mathematician brother John. The pie chart is broadly popular but—despite its common appeal—most experts have not been seduced, and the academy has advised avoidance; nonetheless, the masses have chosen to ignore this advice. This commentary discusses the origins of the pie chart and the appro- priate uses of the form. Keywords: Bruno, circle chart, Euler, Leibniz, Llull, logic diagrams, pie chart, Playfair 1. Introduction The pie chart is more than two centuries old. The diagram first appeared (Playfair, 1801) as an element of two larger graphical displays (see Figure 1 for one instance) in The Statistical Breviary, whose charts portrayed the areas, populations, and rev- enues of European states. William Playfair had previously devised the bar chart and was first to advocate and popularize the use of the line graph to display time series in statistics (Playfair, 1786). The pie chart was his last major graphical invention. Playfair was an accomplished and talented adapter of the ideas of others, and although we may be confident that we know his sources of inspiration in the case of the bar chart and line graph, the intellectual motivations for the pie chart and its parent, the circle chart, remain obscure.
    [Show full text]
  • Informational Graphics
    Informational Graphics • Informational Graphics - (also • Examples include: called infographics, information - tables with facts design, and news graphics) - bar charts or pie charts with statistics • Informational Graphics are visual - maps or diagrams displays that can be anything providing information from a pleasing arrangement of facts and figures in a table to a complex, animated interactive diagram with accompanying text and audio that help explain a story’s meaning. The Economy • The Federal Reserve, the nation's central bank, is predicting sluggish economic growth of 1.6 percent for 2008. Inflation and joblessness have been increasing, however, and most financial experts say the economic malaise is likely to continue into 2009. The Economy William Playfair (1759-1823) is generally viewed as the inventor of most of the common graphical forms used to display data: line plots, bar chart and pie chart. His The Commercial and Political Atlas, published in 1786, contained a number of interesting time-series charts such as these. Statistical Infographics • The two main types of statistical infographic elements are charts (also called graphs) and data maps. • Charts (graphs) were invented to display numerical information concisely and comprehensibly and to show trends visually. – Line, relational, pie, and pictograph are the primary examples of charts, but other variations include bubble, doughnut, radar, surface, and scatter plots. • Data maps usually combine numeric data and locations within a simple locator map to form a powerful story-telling combination. line charts • A line chart contains a rule that connects points plotted on a grid that correspond to amounts along a horizontal, or x-axis and a vertical, or y-axis.
    [Show full text]
  • Life Before EXCEL: Some Historical Statistical Graphs David Robinson THAMES CANCER REGISTRY
    Life before EXCEL: some historical statistical graphs David Robinson THAMES CANCER REGISTRY Introduction Francis Galton (1822-1911) - scientist, statistician and African explorer - was a cousin of Charles Darwin. He was born in Birmingham, the youngest of In this age of the personal computer, where complex pictorial representations of eight children of a prominent Quaker family. He studied medicine at King’s data can be produced at the press of a button or the click of a mouse, we tend College London and mathematics at Cambridge. He was a man of diverse to take statistical graphics very much for granted, and it is difficult to imagine talents, and was responsible (amongst many other projects) for the first weather how revolutionary the first simple charts were. What follows is a description of map, a theory of anticyclones, and the system for classifying fingerprints still in some of the most influential of these early attempts to display data, and the use today. He wrote a treatise on how to make the perfect cup of tea, and stories and characters behind them. published a ‘beauty map’ of the British Isles – based on the number of attractive women he encountered on his travels. (London came out with the highest score; Aberdeen the lowest.) Among his many statistical achievements, he is credited with the introduction of the standard deviation, the correlation coefficient and the regression line. His discovery of the phenomenon of ‘regression to the mean’ is illustrated in his famous chart (Figure 7) shown at the Royal Institution Lecture of 1877. Among Figure 2 his protégés was the great statistician Karl Pearson.
    [Show full text]
  • A Brief History of Data Visualization
    A Brief History of Data Visualization Michael Friendly Psychology Department and Statistical Consulting Service York University 4700 Keele Street, Toronto, ON, Canada M3J 1P3 in: Handbook of Computational Statistics: Data Visualization. See also BIBTEX entry below. BIBTEX: @InCollection{Friendly:06:hbook, author = {M. Friendly}, title = {A Brief History of Data Visualization}, year = {2006}, publisher = {Springer-Verlag}, address = {Heidelberg}, booktitle = {Handbook of Computational Statistics: Data Visualization}, volume = {III}, editor = {C. Chen and W. H\"ardle and A Unwin}, pages = {???--???}, note = {(In press)}, } © copyright by the author(s) document created on: March 21, 2006 created from file: hbook.tex cover page automatically created with CoverPage.sty (available at your favourite CTAN mirror) A brief history of data visualization Michael Friendly∗ March 21, 2006 Abstract It is common to think of statistical graphics and data visualization as relatively modern developments in statistics. In fact, the graphic representation of quantitative information has deep roots. These roots reach into the histories of the earliest map-making and visual depiction, and later into thematic cartography, statistics and statistical graphics, medicine, and other fields. Along the way, developments in technologies (printing, reproduction) mathematical theory and practice, and empirical observation and recording, enabled the wider use of graphics and new advances in form and content. This chapter provides an overview of the intellectual history of data visualization from medieval to modern times, describing and illustrating some significant advances along the way. It is based on a project, called the Milestones Project, to collect, catalog and document in one place the important developments in a wide range of areas and fields that led to mod- ern data visualization.
    [Show full text]
  • Introduction
    Introduction Data graphics visually display measured (Fulltities by meam of the combined use of points, Jines, a coordinate system, numbers, symbols, words, shading, and color. The usc ofabstract, non-representational pictures to show numbers is a surprisingly recent invention, perhaps because of the diversity of skills required - the visual-artistic, empirical-statistical, and mathematical. It was not ullti11750-1Hoo that statistical graphics­ length and area to show quantity, time-series, scatterplots, and multivariate displays-were invented, long after such triumphs of mathematical ingenuity as logarithms, Cartesian coordinates, the calculus, and the basics of probability theory. The remarkable William Playfair (1759-1 H23) developed or improved upon nearly all the fundamental graphical designs, seeking to replace conven­ tional tables of numbers with the systematic visual representations of his "linear ari thmetic." Modern data graphics can do much more than simply substitute for small statistical tables. At their best, graphics arc instrumcnts for reasoning about quantitative inf(xmation. Often the most effec­ tive way to describe, explore, and summarize a set of l1umbers­ even a very large set-is to look at pictures of those numbers. Furthermore, of all mcthods for analyzing and communicating statistical information, well-designcd data graphics arc usually the simplest and at the same time the most powerful. The tlrst part of this book reviews the graphical practice of the two cellturies since Playfair. The reader will, I hope, rejoice in the graphical glories shown in Chapter 1 and then condemn the lapses and lost opportunities exhibited in Chapter 2. Chapter 3, 011 graph­ ical integrity and sophistication, seeks to account t(x these diftcr­ ences in quality of graphical design.
    [Show full text]
  • A Brief History of Data Visualization
    ABriefHistory II.1 of Data Visualization Michael Friendly 1.1 Introduction ........................................................................................ 16 1.2 Milestones Tour ................................................................................... 17 Pre-17th Century: Early Maps and Diagrams ............................................. 17 1600–1699: Measurement and Theory ..................................................... 19 1700–1799: New Graphic Forms .............................................................. 22 1800–1850: Beginnings of Modern Graphics ............................................ 25 1850–1900: The Golden Age of Statistical Graphics................................... 28 1900–1950: The Modern Dark Ages ......................................................... 37 1950–1975: Rebirth of Data Visualization ................................................. 39 1975–present: High-D, Interactive and Dynamic Data Visualization ........... 40 1.3 Statistical Historiography .................................................................. 42 History as ‘Data’ ...................................................................................... 42 Analysing Milestones Data ...................................................................... 43 What Was He Thinking? – Understanding Through Reproduction.............. 45 1.4 Final Thoughts .................................................................................... 48 16 Michael Friendly It is common to think of statistical graphics and data
    [Show full text]